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AI & Smart Systems

AI Development

Ship AI that survives contact with production.

Clutch 5.0 · 48 reviews ISO 27001 Certified600+ projects · 12+ years

Most AI initiatives die between the demo and the deployment. Sydova builds AI systems that make it all the way: scoped around a measurable business outcome, engineered with evaluation harnesses from day one, and shipped with the observability to prove they work.

Our AI team pairs ML engineers with product-minded full-stack developers, so the model is never the whole story — the workflow around it, the guardrails, and the UX get equal engineering weight.

Engagements range from 2-week AI feasibility sprints to multi-quarter platform builds with dedicated teams.

What's included

AI Development services we offer

01

AI Feasibility Sprints

Two weeks from idea to a working proof-of-concept with an honest go/no-go recommendation.

02

Custom Model Pipelines

Data pipelines, fine-tuning, evaluation suites, and deployment on your cloud.

03

AI Product Engineering

Full-stack products with AI at the core — UX, APIs, billing, and admin included.

04

MLOps & Monitoring

Versioned prompts and models, drift detection, cost dashboards, and rollback paths.

How we work

A process built for certainty

  1. 1

    Discovery

    We map goals, users, constraints, and success metrics into a scoped roadmap with fixed milestones.

  2. 2

    Design

    UX flows and UI systems are prototyped, tested against real content, and signed off before build.

  3. 3

    Build

    Senior engineers ship in weekly sprints with code review, CI, and a demo environment you can click.

  4. 4

    QA & Launch

    Automated and manual QA, performance and accessibility audits, then a monitored, reversible launch.

  5. 5

    Support

    Post-launch SLAs, iteration sprints, and roadmap reviews keep the product improving.

Stack & models

Technologies and ways to engage

Fixed-scope project

Defined deliverables, milestone billing, and a warranty period.

  • Signed scope & timeline
  • Weekly demo cadence
  • Best for bounded builds

Dedicated team

A stable pod on monthly capacity, steered by your priorities.

  • Scales quarterly
  • Roadmap-driven
  • Best for products

Hourly / retainer

Flexible senior hours for audits, fixes, and advisory.

  • 40-hour minimum
  • Rolls over 1 month
  • Best for ongoing needs

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Projects delivered

0+

Years in business

0%

Client retention

0%

5-star reviews

Proof

AI Development in production

Sydova treated accuracy like an engineering metric, not a marketing claim. That rigor is why schools trust the product.

Priya Raman

Chief Product Officer, Lumina EdTech

FAQ

AI Development — common questions

How do you decide between building custom models and using APIs?

We benchmark hosted frontier models against your task first. Custom training only enters the picture when evals show the gap justifies the cost — which is rarer than most vendors admit.

How do you measure whether the AI actually works?

Every engagement starts with an evaluation dataset built from your real cases. We report accuracy, latency, and cost per task before and after every change.

Can you work with our sensitive data?

Yes — we deploy inside your VPC or on-prem where required, and we're used to working under DPAs, SOC 2 controls, and regional data-residency constraints.

What does a typical AI project cost?

Feasibility sprints start around $8k. Production builds typically run $40k–$250k depending on scope; a dedicated AI pod is a monthly engagement.

Who owns the IP?

You do — code, prompts, fine-tuned weights, and evaluation data are all delivered to your repos and accounts.

Related services

Where teams go next

Ready to start with ai development?

Tell us where you're headed — a senior specialist replies within one business day.